Can I run MiniMax M2.7 (MoE) locally?
MiniMax M2.7 (MoE) has 228.69 billion parameters (Hugging Face). At the popular Q4_K_M quantization it needs roughly 147.2 GB of GPU memory ESTIMATE. It has been on Hugging Face since 2026-04-09. It's a mixture-of-experts model: all weights must fit in memory, but it generates faster than a dense model of the same size.
Memory needed by quantization
| Quant | Weights | Total needed (est.) |
|---|---|---|
| IQ1_S | 44.6 GB | 48.5 GB |
| IQ2_XXS | 58.9 GB | 63.5 GB |
| IQ2_M | 77.2 GB | 82.7 GB |
| Q2_K | 90.6 GB | 96.8 GB |
| IQ3_XXS | 87.5 GB | 93.5 GB |
| Q3_K_S | 104.3 GB | 111.2 GB |
| IQ3_M | 104.6 GB | 111.5 GB |
| Q3_K_M | 114.3 GB | 121.7 GB |
| IQ4_XS | 121.5 GB | 129.2 GB |
| Q4_0 | 128.6 GB | 136.7 GB |
| Q4_K_M | 138.6 GB | 147.2 GB |
| MXFP4 | 132.4 GB | 140.6 GB |
| Q5_K_M | 162.7 GB | 172.4 GB |
| Q6_K | 187.5 GB | 198.5 GB |
| Q8_0 | 243.0 GB | 256.8 GB |
| F16 | 457.4 GB | 481.9 GB |
KV cache by context length ESTIMATE
| Context | f16 | q8_0 | q4_0 |
|---|---|---|---|
| 4k | 1.04 GB | 0.55 GB | 0.29 GB |
| 8k | 2.08 GB | 1.11 GB | 0.59 GB |
| 16k | 4.16 GB | 2.21 GB | 1.17 GB |
| 32k | 8.32 GB | 4.42 GB | 2.34 GB |
| 64k | 16.64 GB | 8.84 GB | 4.68 GB |
| 128k | 33.29 GB | 17.68 GB | 9.36 GB |
From config.json: 62 KV-caching attention layers, 8 KV heads × 128 head dim. Max context 200k. The tables above assume 4k context.
Which GPUs and Macs can run it?
✅ fits · ⚠️ fits with little headroom · ❌ doesn't fit on this one device (multiple GPUs or RAM offload may work; check your setup). Apple Silicon assumes macOS lets the GPU use ~67–75% of unified memory. All fit verdicts are estimates.
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